The GP Problem: Quantifying Gene-to-Phenotype Relationships

Article type: Research Article

Authors: Cooper, Mark | Chapman, Scott C. | Podlich, Dean W. | Hammer, Graeme L.

Affiliations: School of Land and Food Sciences, The University of Queensland, Brisbane, Queensland 4072, Australia | CSIRO Plant Industry, 120 Meiers Road, Indooroopilly, Queensland 4068, Australia

Note: [] Corresponding author, Email: [email protected], Current Address: Pioneer Hi-Bred International Inc., 7300 N.W. 62nd Avenue, P.O. Box 1004, Johnston, Iowa 50131, USA

Note: [] Current Address: Pioneer Hi-Bred International Inc., 7300 N.W. 62nd Avenue, P.O. Box 1004, Johnston, Iowa 50131, USA

Note: [] Agricultural and Production Systems Research Unit (APSRU), Queensland Department of Primary Industries, Tor Street, Toowoomba, Queensland, Australia

Abstract: In this paper we refer to the gene-to-phenotype modeling challenge as the GP problem. Integrating information across levels of organization within a genotype-environment system is a major challenge in computational biology. However, resolving the GP problem is a fundamental requirement if we are to understand and predict phenotypes given knowledge of the genome and model dynamic properties of biological systems. Organisms are consequences of this integration, and it is a major property of biological systems that underlies the responses we observe. We discuss the E(NK) model as a framework for investigation of the GP problem and the prediction of system properties at different levels of organization. We apply this quantitative framework to an investigation of the processes involved in genetic improvement of plants for agriculture. In our analysis, N genes determine the genetic variation for a set of traits that are responsible for plant adaptation to E environment-types within a target population of environments. The N genes can interact in epistatic NK gene-networks through the way that they influence plant growth and development processes within a dynamic crop growth model. We use a sorghum crop growth model, available within the APSIM agricultural production systems simulation model, to integrate the gene-environment interactions that occur during growth and development and to predict genotype-to-phenotype relationships for a given E(NK) model. Directional selection is then applied to the population of genotypes, based on their predicted phenotypes, to simulate the dynamic aspects of genetic improvement by a plant-breeding program. The outcomes of the simulated breeding are evaluated across cycles of selection in terms of the changes in allele frequencies for the N genes and the genotypic and phenotypic values of the populations of genotypes. Links: http://pig.ag.uq.edu.au/qu-gene/ http://www.apsru.gov.au/Products/apsim.htm

Keywords: E(NK) model, epistasis, genotype-by-environment interactions, plant , crop, target population of environments, genetic space

Journal: In Silico Biology, vol. 2, no. 2, pp. 151-164, 2002